It is not hard to find either myself or Antony. Both of us are here, and both of us are at the top of Google search results for our names.
Probably my bad, I only bumped into LinkedIn references. I'll wait for a reply from Antony as well, thanks. I will explore other ideas as well.
1. A thing Boost really could do with is a decent (optionally mmappable) dense hash map implementation, so the hash map could contain billions of items and mostly reside on disk yet lookups would still be very fast.
I have some questions regarding this first idea. I believe a concept and implementation already exist and are actually in use at Google: http://goog-sparsehash.sourceforge.net/doc/dense_hash_map.html Quoting from that page: ** dense_hash_map is distinguished from other hash-map implementations by its speed and by the ability to save and restore contents to disk. On the other hand, this hash-map implementation can use significantly more space than other hash-map implementations, and it also has requirements -- for instance, for a distinguished "empty key" -- that may not be easy for all applications to satisfy. This class is appropriate for applications that need speedy access to relatively small "dictionaries" stored in memory, and for applications that need these dictionaries to be persistent." ** So what you want is something like this, but able to "contain billions of items and mostly reside on disk yet lookups would still be very fast"? I assume the "billions of items" is what is lacking from that dense_hash_map already in use by Google? Is this the difference between that and your idea? Assuming this is indeed what you were proposing, would the work encompass defining an API and also exploring mmap for lazy iteration for performance gains in the context of handling billions of items? Kind regards, Miguel E. Coimbra